Health at a Glance 2013
OECD INDICATORS
Health at a Glance
2013
OECD INDICATORS
This work is published on the responsibility of the Secretary-General of the OECD. The
opinions expressed and arguments em...
FOREWORD
HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 2013 3
Foreword
This 2013 edition of Health at a Glance – OECD In...
TABLE OF CONTENTS
HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 2013 5
Table of contents
Editorial . . . . . . . . . . ....
TABLE OF CONTENTS
HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 20136
4.4. Hospital discharges . . . . . . . . . . . . ....
HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 2013 7
TABLE OF CONTENTS
8.8. Long-term care beds in institutions and hosp...
EDITORIAL: FROM EXPENDITURE GROWTH TO PRODUCTIVITY GROWTH IN THE HEALTH SECTOR
HEALTH AT A GLANCE 2013: OECD INDICATORS © ...
EDITORIAL: FROM EXPENDITURE GROWTH TO PRODUCTIVITY GROWTH IN THE HEALTH SECTOR
HEALTH AT A GLANCE 2013: OECD INDICATORS © ...
HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 2013 11
EDITORIAL: FROM EXPENDITURE GROWTH TO PRODUCTIVITY GROWTH IN THE H...
EXECUTIVE SUMMARY
HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 2013 13
Executive summary
Health at a Glance 2013 presen...
EXECUTIVE SUMMARY
HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 201314
● There were two specialists for every generalist...
HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 2013 15
EXECUTIVE SUMMARY
● Around 19% of out-of-pocket medical expenditur...
READER’S GUIDE
HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 2013 17
Reader’s guide
Health at a Glance 2013 presents com...
READER’S GUIDE
HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 201318
Chapter 3 looks at the Health Workforce, providing d...
HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 2013 19
READER’S GUIDE
out-of-pocket spending in household consumption. Th...
READER’S GUIDE
HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 201320
Population figures
The population figures presented ...
HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 2013 23
1. HEALTH STATUS
1.1. Life expectancy at birth
1.2. Life expectanc...
HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 201324
1. HEALTH STATUS
1.1. Life expectancy at birth
Life expectancy has ...
1. HEALTH STATUS
1.1. Life expectancy at birth
HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 2013 25
1.1.2. Life expecta...
HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 201326
1. HEALTH STATUS
1.2. Life expectancy by sex and education level
Th...
1. HEALTH STATUS
1.2. Life expectancy by sex and education level
HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 2013 27
1...
HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 201328
1. HEALTH STATUS
1.3. Mortality from cardiovascular diseases
Cardio...
1. HEALTH STATUS
1.3. Mortality from cardiovascular diseases
HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 2013 29
1.3.1...
HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 201330
1. HEALTH STATUS
1.4. Mortality from cancer
Cancer accounts for ove...
1. HEALTH STATUS
1.4. Mortality from cancer
HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 2013 31
1.4.1. All cancer mort...
HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 201332
1. HEALTH STATUS
1.5. Mortality from transport accidents
Worldwide,...
1. HEALTH STATUS
1.5. Mortality from transport accidents
HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 2013 33
1.5.1. Tr...
HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 201334
1. HEALTH STATUS
1.6. Suicide
Suicide is a significant cause of dea...
1. HEALTH STATUS
1.6. Suicide
HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 2013 35
1.6.1. Suicide mortality rates, 2011...
HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 201336
1. HEALTH STATUS
1.7. Infant mortality
Infant mortality, the rate a...
1. HEALTH STATUS
1.7. Infant mortality
HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 2013 37
1.7.1. Infant mortality rat...
HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 201338
1. HEALTH STATUS
1.8. Infant health: Low birth weight
Low birth wei...
1. HEALTH STATUS
1.8. Infant health: Low birth weight
HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 2013 39
1.8.1. Low b...
HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 201340
1. HEALTH STATUS
1.9. Perceived health status
Most OECD countries c...
1. HEALTH STATUS
1.9. Perceived health status
HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 2013 41
1.9.1. Percentage of...
Health indicators Among OECD Countries
Health indicators Among OECD Countries
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Health indicators Among OECD Countries
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Health indicators Among OECD Countries

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This 2013 edition of Health at a Glance – OECD Indicators presents the most recent comparable
data on key indicators of health and health systems across the 34 OECD member countries. Where
possible, it also reports comparable data for Brazil, China, India, Indonesia, the Russian Federation,
and South Africa, as key emerging countries

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Health indicators Among OECD Countries

  1. 1. Health at a Glance 2013 OECD INDICATORS
  2. 2. Health at a Glance 2013 OECD INDICATORS
  3. 3. This work is published on the responsibility of the Secretary-General of the OECD. The opinions expressed and arguments employed herein do not necessarily reflect the official views of the Organisation or of the governments of its member countries. This document and any map included herein are without prejudice to the status of or sovereignty over any territory, to the delimitation of international frontiers and boundaries and to the name of any territory, city or area. ISBN 978-92-64-20071-5 (print) ISBN 978-92-64-20502-4 (PDF) ISBN 978-92-64-20422-5 (HTML) Annual: Health at a glance ISSN 1995-3992 (print) ISSN 1999-1312 (online) The statistical data for Israel are supplied by and under the responsibility of the relevant Israeli authorities. The use of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements in the West Bank under the terms of international law. Photo credits: Cover © gunnar3000 – Fotolia.com. Corrigenda to OECD publications may be found on line at: www.oecd.org/publishing/corrigenda. © OECD 2013 You can copy, download or print OECD content for your own use, and you can include excerpts from OECD publications, databases and multimedia products in your own documents, presentations, blogs, websites and teaching materials, provided that suitable acknowledgment of the source and copyright owner is given. All requests for public or commercial use and translation rights should be submitted to rights@oecd.org. Requests for permission to photocopy portions of this material for public or commercial use shall be addressed directly to the Copyright Clearance Center (CCC) at info@copyright.com or the Centre français d'exploitation du droit de copie (CFC) at contact@cfcopies.com. Please cite this publication as: OECD (2013), Health at a Glance 2013: OECD Indicators, OECD Publishing. http://dx.doi.org/10.1787/health_glance-2013-en
  4. 4. FOREWORD HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 2013 3 Foreword This 2013 edition of Health at a Glance – OECD Indicators presents the most recent comparable data on key indicators of health and health systems across the 34 OECD member countries. Where possible, it also reports comparable data for Brazil, China, India, Indonesia, the Russian Federation, and South Africa, as key emerging countries. The production of Health at a Glance would not have been possible without the contribution of OECD Health Data National Correspondents, Health Accounts Experts, and Health Care Quality Indicators Experts from the 34 OECD countries. The OECD gratefully acknowledges their effort in supplying most of the data contained in this publication. The OECD also acknowledges the contribution of other international organisations, especially the World Health Organization, the World Bank and Eurostat, for sharing some of the data presented here, and the European Commission for supporting data development. This publication was prepared by a team from the OECD Health Division under the co- ordination of Gaétan Lafortune. Chapter 1 was prepared by Gaétan Lafortune, Kees van Gool and Nelly Biondi; Chapter 2 by Franco Sassi, Marion Devaux, Michele Cecchini and Nelly Biondi; Chapter 3 by Michael Schoenstein, Gaétan Lafortune, Gaëlle Balestat and Anne Durand; Chapter 4 by Gaétan Lafortune, Valérie Paris, Gaëlle Balestat, Marie-Clémence Canaud and Jessica Farebrother; Chapter 5 by Kees van Gool, Ian Forde, Rie Fujisawa, Nelly Biondi, Evianne van der Kruk and Niek Klazinga; Chapter 6 by Marion Devaux, Valérie Paris, Gaétan Lafortune, Michael Schoenstein, Tomoko Ono, Michael Mueller, Emily Hewlett and Alessia Forti; Chapter 7 by David Morgan, Michael Mueller and Alan Diener; and Chapter 8 by Francesca Colombo, Yuki Murakami, Marie-Clémence Canaud, Nelly Biondi, Michael Mueller and Martin Salomon. This publication benefited from many comments and suggestions from Mark Pearson (Head of the OECD Health Division).
  5. 5. TABLE OF CONTENTS HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 2013 5 Table of contents Editorial . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Executive summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 Reader’s guide . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 Chapter 1. Health status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 1.1. Life expectancy at birth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 1.2. Life expectancy by sex and education level . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 1.3. Mortality from cardiovascular diseases. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 1.4. Mortality from cancer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 1.5. Mortality from transport accidents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 1.6. Suicide . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 1.7. Infant mortality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 1.8. Infant health: Low birth weight . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 1.9. Perceived health status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 1.10. Diabetes prevalence and incidence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 Chapter 2. Non-medical determinants of health. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 2.1. Smoking and alcohol consumption among children . . . . . . . . . . . . . . . . . . . . 46 2.2. Overweight and obesity among children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 2.3. Fruit and vegetable consumption among children . . . . . . . . . . . . . . . . . . . . . . 50 2.4. Physical activity among children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 2.5. Tobacco consumption among adults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 2.6. Alcohol consumption among adults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 2.7. Overweight and obesity among adults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58 2.8. Fruit and vegetable consumption among adults . . . . . . . . . . . . . . . . . . . . . . . . 60 Chapter 3. Health workforce . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 3.1. Doctors (overall number) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 3.2. Doctors by age, sex and category . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 3.3. Gynaecologists and obstetricians, and midwives . . . . . . . . . . . . . . . . . . . . . . . 68 3.4. Psychiatrists and mental health nurses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70 3.5. Medical graduates. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72 3.6. Remuneration of doctors (general practitioners and specialists) . . . . . . . . . . 74 3.7. Nurses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76 3.8. Nursing graduates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 3.9. Remuneration of nurses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 Chapter 4. Health care activities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 4.1. Consultations with doctors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84 4.2. Medical technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86 4.3. Hospital beds. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
  6. 6. TABLE OF CONTENTS HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 20136 4.4. Hospital discharges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90 4.5. Average length of stay in hospitals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92 4.6. Cardiac procedures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94 4.7. Hip and knee replacement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96 4.8. Caesarean sections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98 4.9. Cataract surgeries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 4.10. Pharmaceutical consumption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102 4.11. Pharmaceutical generic market share . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104 Chapter 5. Quality of care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 5.1. Avoidable hospital admissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108 5.2. Prescribing in primary care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110 5.3. Mortality following acute myocardial infarction (AMI) . . . . . . . . . . . . . . . . . . . 112 5.4. Mortality following stroke . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114 5.5. Surgical complications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116 5.6. Obstetric trauma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118 5.7. Unplanned hospital re-admissions for patients with mental disorders. . . . . 120 5.8. Excess mortality from mental disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122 5.9. Screening, survival and mortality for cervical cancer . . . . . . . . . . . . . . . . . . . 124 5.10. Screening, survival and mortality for breast cancer . . . . . . . . . . . . . . . . . . . . . 126 5.11. Survival and mortality for colorectal cancer. . . . . . . . . . . . . . . . . . . . . . . . . . . . 128 5.12. Childhood vaccination programmes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130 5.13. Influenza vaccination for older people . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132 5.14. Patient experience with ambulatory care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134 Chapter 6. Access to care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137 6.1. Coverage for health care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138 6.2. Out-of-pocket medical expenditure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140 6.3. Geographic distribution of doctors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142 6.4. Inequalities in doctor consultations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144 6.5. Inequalities in dentist consultations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146 6.6. Inequalities in cancer screening. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148 6.7. Waiting times for elective surgery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150 Chapter 7. Health expenditure and financing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153 7.1. Health expenditure per capita . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154 7.2. Health expenditure in relation to GDP. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156 7.3. Health expenditure by function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158 7.4. Pharmaceutical expenditure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160 7.5. Expenditure by disease and age . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162 7.6. Financing of health care. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164 7.7. Trade in health services . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 166 Chapter 8. Ageing and long-term care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169 8.1. Demographic trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170 8.2. Life expectancy and healthy life expectancy at age 65 . . . . . . . . . . . . . . . . . . . 172 8.3. Self-reported health and disability at age 65 . . . . . . . . . . . . . . . . . . . . . . . . . . . 174 8.4. Dementia prevalence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 176 8.5. Recipients of long-term care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178 8.6. Informal carers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180 8.7. Long-term care workers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182
  7. 7. HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 2013 7 TABLE OF CONTENTS 8.8. Long-term care beds in institutions and hospitals . . . . . . . . . . . . . . . . . . . . . . 184 8.9. Long-term care expenditure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 186 Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189 Annex A. Additional information on demographic and economic context, and health expenditure and financing. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203 Look for the StatLinks2at the bottom of the tables or graphs in this book. To download the matching Excel® spreadsheet, just type the link into your Internet browser, starting with the http://dx.doi.org prefix, or click on the link from the e-book edition. Follow OECD Publications on: This book has... StatLinks2 A service that delivers Excel files from the printed page!® http://twitter.com/OECD_Pubs http://www.facebook.com/OECDPublications http://www.linkedin.com/groups/OECD-Publications-4645871 http://www.youtube.com/oecdilibrary http://www.oecd.org/oecddirect/ OECD Alerts
  8. 8. EDITORIAL: FROM EXPENDITURE GROWTH TO PRODUCTIVITY GROWTH IN THE HEALTH SECTOR HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 2013 9 Editorial: From expenditure growth to productivity growth in the health sector Almost six years since the start of the global financial and economic crisis, economic conditions vary widely across OECD countries, with the United States, Canada and Japan on a path to recovery, while the economic prospects of many European countries remain subdued. After a period in which, as part of the stimulus packages, greater resources were channelled to welfare and social protection programmes, the shift towards restoring sound fiscal conditions has often implied substantial cuts in public spending. Like other government programmes, health care has been the target of spending cuts in many OECD countries. The crisis has had a profound impact on the lives of citizens across the world, and has tested the resilience of many families as they see their wealth and incomes decline. Millions of people have joined the ranks of the unemployed and millions more are experiencing financial stress. The combined effects of the crisis with the associated recent expenditure cuts as well as health care reforms have led to uncertainty about the impact on the health and well-being of the population. The most recent OECD health statistics, presented in this edition of Health at a Glance, provide a comprehensive picture of how health systems have evolved during the crisis and the challenges which lie ahead. Most OECD countries have moved to lower health spending Growth in health spending has slowed markedly in almost all OECD countries since 2008. After years of continuous growth of over 4% per annum, average health spending across the OECD grew at only 0.2% between 2009 and 2011. Total health spending fell in 11 out of the 34 OECD countries between 2009 and 2011, compared to pre-crisis levels. Not surprisingly, the countries hit hardest by the economic crisis have witnessed the biggest cuts in health expenditure growth. For example, Greece and Ireland experienced the sharpest declines, with per capita health care spending falling by 11.1% and 6.6%, respectively, between 2009 and 2011. Health spending growth also slowed significantly in Canada and the United States. Only in Israel and Japan has health spending growth accelerated since 2009. In order to limit or reduce public health expenditures, countries have worked to lower the prices paid for publicly financed health care, including cutting the price of medical goods, particularly pharmaceuticals. Governments have targeted hospital spending through budgetary restrictions and cuts to wages. Several countries including Greece, Ireland, Iceland and Estonia have reduced nursing wages in response to the crisis as well as those of salaried GPs. Expenditure on prevention and public health has also been cut since 2009. Further, in several OECD countries, patients are now expected to assume a greater share of health costs.
  9. 9. EDITORIAL: FROM EXPENDITURE GROWTH TO PRODUCTIVITY GROWTH IN THE HEALTH SECTOR HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 201310 The crisis has had a mixed impact on health indicators What has been the effect of the crisis on health? The results are mixed. For example, while suicide rates rose slightly at the start of the crisis, they appear to have stabilised since then. There are also indications that Greece’s infant mortality rate, long in decline, has been rising since the crisis started. Neither is good news. But other health indicators tell a different story: mortality from road traffic accidents, for example, has declined. Such deaths had already been steadily falling in most OECD countries, but the rate of decline accelerated after 2008 in some countries that were hard hit by the recession, likely because less economic activity means fewer cars on the roads, and so fewer accidents. The crisis may also have led to positive changes in certain health behaviours. In particular, alcohol and tobacco consumption in a number of OECD countries fell in the immediate aftermath of the crisis. This was already a long-standing trend in most countries, but the drop in consumption has accelerated due to the combined impact of lower incomes and more stringent policies around purchasing and use. It remains a question as to whether these gains can be maintained once economic growth and household budgets improve. As the short-term impact of the crisis on health is both bad (mental health) and good (accidents, alcohol), it is not surprising to find that there is no evidence yet of a widespread health impact in the countries hardest hit by the crisis. As with so many things in health, the pathways by which economic crisis and policies affect health outcomes are complex to evaluate. Moreover, most countries, including those most heavily affected by the crisis, continue to make progress in primary health care and the quality of acute care for life- threatening conditions. There are no signs that the crisis is raising cancer-related mortality rates, for example, and most countries have continued to raise survival rates for cardiovascular disease. Nevertheless, the direction that policies have taken in some countries raises some concern. For instance, prevention is often a more cost-effective way of improving health than spending money once a disease takes root. However, prevention expenditures have been reduced since 2009 (although they only account for around 3-4% of total health expenditure). One example of the consequences is the dramatic rise in the number of new HIV cases reported since 2010 in Athens, Greece, among injecting drug users. Although opioid substitution and needle exchange programmes have expanded since the start of the outbreak, the initial response fell well short of recommended levels of access, illustrating the potential long-term impact on health and spending when highly cost-effective prevention programmes are not fully implemented. Cuts in spending on preventing obesity, harmful use of alcohol, and tobacco consumption are cases of “penny-wise, pound foolish” thinking. Likewise, cuts to the supply of health care services and changes in health care financing arrangements are also affecting access to care. After years of steady decline, average waiting times for some operations in Portugal, Spain, England, and Ireland show a small increase. There is evidence that more people in countries such as Greece and Italy are foregoing medical care due to financial constraints, reflecting reduced household incomes, but also perhaps rising out-of-pocket costs. Low-income groups are the worst affected, although they are likely to have the highest health care needs, and they may be foregoing necessary care such as medicines or routine medical check-ups for chronic conditions. This may have long-term health and economic consequences for the most vulnerable groups in society. Towards affordable, sustainable care Pressures to reduce public spending are likely to persist well into the recovery phase. Given the large fiscal imbalances built during the crisis, fiscal consolidation required to bring
  10. 10. HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 2013 11 EDITORIAL: FROM EXPENDITURE GROWTH TO PRODUCTIVITY GROWTH IN THE HEALTH SECTOR debt-to-GDP ratios back to sustainable levels would have to be pursued for a number of years, as stressed in the 2013 OECD Economic Outlook. Countries’ main consolidation targets vary but generally focus on inefficient public expenditures and include savings on health care. In a climate of fiscal restraint and efficiency efforts, health expenditure growth should be more aligned to a country’s economic growth and its ability to raise revenue. This was not the case before the crisis, when health care funding outpaced economic growth in many countries. The crisis has pushed many countries to undertake structural reforms of their health systems, aimed at changing the incentives or the way that prices are negotiated. Examples include Greece’s introduction of a new output-based hospital funding system, Italy’s drive for greater competiveness in the pharmaceutical distribution market, Portugal’s investment in health care performance management systems and the centralisation of pharmaceutical purchasing powers in Spain. These reforms could make important long-term contributions to the health systems’ productivity and efficiency. Governments must continue to seek clever ways by which health systems can continue to improve the well-being of patients within the new fiscal environment. Some countries are moving towards greater labour productivity by re-examining the traditional functions of general practitioners, specialists, nurses and allied health professionals. Other countries are also looking at the extent to which medical practice variation points towards ineffective or inefficient care. For example, there is a three-fold difference in the rate of caesarean sections between Iceland and the Netherlands, which have the lowest number of caesareans, and Mexico which has the highest rate. Some of this variation may be justified by clinical need, but it could also mean that women are either having unnecessary operations, or being denied care they should be getting. Evidence-based clinical pathways can improve health care productivity. While the agenda for quality of care has now been firmly embedded in most health care systems, countries can make further gains in patient safety, thereby reducing the costs and health burdens associated with adverse events. Health care quality can also be improved by strengthening primary care systems to better manage complex conditions. The increasing prevalence of complex chronic diseases is one of the many challenges arising from ageing populations and will require constant vigilance and multidisciplinary care to prevent the onset of costly complications. Many of the reforms implemented since the start of the crisis have had an immediate impact on public expenditure. Some have been controversial, with considerable unrest and political pressure from industry groups, and some may also have had undesirable consequences for access, outcomes and equity. For example, greater out-of-pocket costs are likely to reduce health care use among those in highest need, leading to greater inequity and inefficiency over the longer term. In the new, more constrained, fiscal climate, the challenge for health care policy makers is to preserve quality health care coverage for the whole population while converting a system built on notions of unconstrained growth to one that is based on greater productivity and fiscal sustainability. This challenge is not new. Countries have pursued the twin objectives of efficiency and equity in health for decades. The economic crisis means that health care policy makers must swiftly and convincingly adopt a health care productivity agenda. Stefano Scarpetta Director for Employment, Labour and Social Affairs
  11. 11. EXECUTIVE SUMMARY HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 2013 13 Executive summary Health at a Glance 2013 presents the trends and influences shaping health status, services and policies in OECD countries and the BRIICS. Although indicators such as life expectancy or infant mortality suggest that things are improving overall, inequalities in wealth, education and other social indicators still have a significant impact on health status and access to health services. These health disparities may be explained by differences in living and working conditions, as well as differences that show up in the health-related lifestyle data presented here (e.g., smoking, harmful alcohol drinking, physical inactivity, and obesity). Health expenditures show considerable variations across countries, in terms of spending per capita, as a share of GDP and recent trends. On average across the OECD, per capita health spending grew by 4.1% annually in real terms over 2000-2009, but this slowed to 0.2% in 2009-10 and 2010-11 as many countries reduced health spending to help cut budget deficits and government debt, especially in Europe. Countries outside of Europe have continued to see health spending grow, albeit at a reduced pace in many cases, notably in Canada and the United States. Different areas of spending have been affected in different ways: in 2010-11, spending on pharmaceuticals and prevention dropped by 1.7%, while hospital costs rose by 1.0%. Life expectancy in OECD countries is rising, but so is the burden of chronic diseases ● Average life expectancy exceeded 80 years across OECD countries in 2011, an increase of ten years since 1970. Those born in Switzerland, Japan and Italy can expect to live the longest among OECD countries. ● Across OECD countries, women can expect to live 5.5 years longer than men. People with the highest level of education can expect to live 6 years longer than those with the lowest level of education. ● Chronic diseases such as diabetes and dementia are increasingly prevalent. In 2011, close to 7% of 20-79 year-olds in OECD countries, or over 85 million people, had diabetes. There are more doctors per capita in most countries, but twice as many specialists as generalists ● Since 2000, the number of doctors has grown in most OECD countries, both in absolute number and on a per capita basis, with only a few exceptions. There was virtually no growth in the number of doctors per capita in Estonia and France, and a decline in Israel.
  12. 12. EXECUTIVE SUMMARY HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 201314 ● There were two specialists for every generalist on average across the OECD, in 2011. The slow growth in, or reduction of, the number of generalists raises concerns about access to primary care for all the population. Shorter hospital stays and growing use of generic drugs help to contain costs, but large variations in medical practice point towards overuse ● The length of stay in hospital dropped from 9.2 days in 2000 to 8.0 days in 2011 in OECD countries. ● The market share of generic drugs has increased significantly over the past decade in many countries. However, generics still represent less than 25% of the market in Luxembourg, Italy, Ireland, Switzerland, Japan and France, compared with about 75% in Germany and the United Kingdom. ● Wide variations in the utilisation rate of different diagnostic and surgical procedures cannot be explained by differences in clinical needs. For example, in 2011, caesarean sections made up more than 45% of all births in Mexico and Turkey, triple the rate in Iceland and the Netherlands, suggesting possible overuse. The quality of acute care and primary care has improved in most countries, but could improve more ● Progress in the treatment of life-threatening conditions such as heart attack, stroke and cancer has led to higher survival rates in most OECD countries. On average, mortality rates following hospital admissions for heart attack fell by 30% between 2001 and 2011 and for stroke by almost 25%. Survival has also improved for many types of cancer, including cervical cancer, breast cancer and colorectal cancer. ● The quality of primary care has also improved in most countries, as shown by the reduction in avoidable hospital admissions for chronic diseases such as asthma and diabetes. Still, there is room in all countries to improve primary care to further reduce costly hospital admissions for these conditions. Nearly all OECD countries have achieved universal health coverage, but the scope and degree of coverage varies ● All OECD countries have universal (or quasi-universal) health coverage for a core set of health services and goods, except Mexico and the United States. Following the 2004 reforms in Mexico, the proportion of the population covered has grown rapidly to reach nearly 90%. In the United States, where 15% of the population was still uninsured in 2011, the Affordable Care Act will further expand health insurance coverage, from January 2014. ● The burden of out-of-pocket spending creates barriers to health care access in some countries. On average, 20% of health spending is paid directly by patients; this ranges from less than 10% in the Netherlands and France to over 35% in Chile, Korea and Mexico.
  13. 13. HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 2013 15 EXECUTIVE SUMMARY ● Around 19% of out-of-pocket medical expenditure across OECD countries in 2011 was for dental care, while another 12% was for eyeglasses, hearing aids and other therapeutic appliances. ● People in low-income groups are more likely to report unmet medical and dental needs than people in higher-income groups, and are also less likely to consult a medical specialist or a dentist. Population ageing increases demand for long-term care and puts pressures on public spending, despite informal care ● The life expectancy of people at age 65 has continued to increase, reaching nearly 21 years for women and 18 years for men across OECD countries in 2011. However, many of these additional years are lived with some chronic conditions. For example, over a quarter of people aged 85 years and older suffers from dementia. ● Across OECD countries, more than 15% of people aged 50 and older provide care for a dependent relative or friend, and most informal carers are women. ● Public expenditures on long-term care grew by 4.8% annually between 2005 and 2011 across OECD countries, higher than the growth in health care spending.
  14. 14. READER’S GUIDE HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 2013 17 Reader’s guide Health at a Glance 2013 presents comparisons of key indicators of health and health systems across the 34 OECD countries, as well as for key emerging countries (Brazil, China, India, Indonesia, the Russian Federation and South Africa). The indicators presented in this publication have been selected on the basis of their policy relevance as well as data availability and comparability. The data come mainly from official national statistics, unless otherwise indicated. Structure of the publication The framework underlying this publication assesses the performance of health systems in the context of a broader view of public health (Figure 0.1). It is based on a framework that was endorsed for the OECD Health Care Quality Indicators project (Kelley and Hurst, 2006; Arah et al., 2006). This framework recognises that the goal of health systems is to improve the health status of the population. Many factors influence the health status of the population, including a number that fall outside health care systems, such as the physical environment in which people live, and individual lifestyles and behaviours. The performance of health care systems also contributes obviously to the health status of the population. This performance includes several dimensions, including the degree of access to care and the quality of care provided. Performance measurement also needs to take into account the financial resources required to achieve these access and quality goals. The performance of health systems depends on the people providing the services, and the training, technology and equipment at their disposal. Finally, a number of contextual factors that also affect the health status of the population and the demand for and supply of health services also need to be taken into account, including the demographic context, and economic and social development. Health at a Glance 2013 compares OECD countries on each component of this framework. It is structured around eight chapters. Chapter 1 on Health Status highlights large variations across countries in life expectancy, mortality and other measures of population health status. Compared with the previous edition, this chapter includes new measures of inequality in health status by education and income level for key indicators such as life expectancy and perceived health status. Chapter 2 on Non-medical Determinants of Health focuses on health-related lifestyles and behaviours among children and adults, including tobacco smoking, alcohol drinking, physical activity, nutrition, and overweight and obesity problems. Most of these factors can be modified by public health and prevention policies.
  15. 15. READER’S GUIDE HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 201318 Chapter 3 looks at the Health Workforce, providing data on the supply and remuneration of doctors and nurses in OECD countries. It also presents trends on the number of new graduates from medical and nursing education programmes, a key determinant of future supply. Chapter 4 on Health Care Activities describes some of the main characteristics of health service delivery in different OECD countries. It begins by looking at consultations with doctors, and the supply and use of diagnostic technologies such as medical resonance imaging and computed tomography scanners. The hospital sector continues to absorb the largest share of health spending in OECD countries, hence a focus on the availability of hospital beds, their utilisation rate, the number of hospital discharges and average length of stay. The chapter also looks at variations in the use of high-volume and high-cost procedures, such as caesarean sections, cardiac procedures, and hip and knee replacement. It concludes by looking at the pharmaceutical market, comparing the use of certain pharmaceutical drugs and the share of the generic market in different countries. Chapter 5 examines Quality of Care or the degree to which care is delivered in accordance with established standards and improves health outcomes. It provides comparisons on quality of care for chronic conditions and pharmaceutical prescriptions, acute care for life-threatening diseases, patient safety, care for mental disorders, cancer care, the prevention of communicable diseases and, for the first time, some important aspects of patient experiences. Chapter 6 on Access to Care presents a set of indicators that can be used to assess to what extent OECD countries are meeting their policy goal of ensuring adequate access to essential health services on the basis of individual need. It begins by describing the proportion of population covered by public or private health insurance and the share of Figure 0.1. Conceptual framework for health system performance assessment Source: Adapted from Kelley, E. and J. Hurst (2006), “Health Care Quality Indicators Project: Conceptual Framework”, OECD Health Working Paper, No. 23, OECD Publishing, http://dx.doi.org/10.1787/440134737301. Health (Chapter 1) Non-medical determinants of health (Chapter 2) Health care system performance How does the health system perform? What is the level of quality of care and access to services? What does this performance cost? Quality (Chapter 5) Access (Chapter 6) Cost/expenditure (Chapter 7) Health care resources and activities Health workforce (Chapter 3) Health care activities (Chapter 4) Demographic, economic and social context (Annex A)
  16. 16. HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 2013 19 READER’S GUIDE out-of-pocket spending in household consumption. The chapter then discusses issues around geographic access to care, focusing in particular on the “density” of doctors in different regions in each country. Another approach to measuring access to care is to look at inequalities among different socioeconomic groups in the use of health services. Three indicators look at the use of doctors, dentists and screening rates for cancer, either by income group or education level. The last indicator relates to timely access to care, comparing waiting times for certain elective surgery in a group of OECD countries where this is considered to be an important issue. Chapter 7 on Health Expenditure and Financing compares how much OECD countries spend on health, both on a per capita basis and in relation to GDP. The chapter also provides an analysis of the different types of health services and goods consumed across OECD countries, including a separate focus on pharmaceuticals. It also looks at how these health services and goods are paid for in different countries (i.e. the mix between public funding, private health insurance where it exists, and direct out-of-pocket payments). Lastly, in the context of the growth in medical tourism and international trade in health services, current levels and trends are examined. Chapter 8 focuses on Ageing and Long-term Care, starting by a review of demographic trends and the rising share of the population aged over 65 and 80 in all OECD countries. The chapter presents the most recent data on life expectancy and life expectancy in good health at age 65, self-reported health and disability status, as important factors affecting the current and future demand for long-term care. This is followed by a set of indicators on older persons currently receiving long-term care at home or in institutions, on care providers (including both formal and informal caregivers), and on the capacity to provide long-term care in institutions in different countries. The final indicator reviews levels and trends in long-term care expenditure over the past decade. A Statistical Annex provides additional information on the demographic and economic context within which health and long-term care systems operate. Presentation of indicators Each of the topics covered in the different chapters of this publication is presented over two pages. The first provides a brief commentary highlighting the key findings conveyed by the data, defines the indicator and signals any significant national variation from the definition which might affect data comparability. On the facing page is a set of figures. These typically show current levels of the indicator and, where possible, trends over time. Where an OECD average is included in a figure, it is the unweighted average of the OECD countries presented, unless otherwise specified. Data limitations Limitations in data comparability are indicated both in the text (in the box related to “Definition and comparability”) as well as in footnotes to figures. Data sources Readers interested in using the data presented in this publication for further analysis and research are encouraged to consult the full documentation of definitions, sources and methods presented in OECD Health Statistics on OECD.Stat (http://stats.oecd.org/index.aspx, then choose “Health”). More information on OECD Health Statistics is available at www.oecd.org/health/healthdata. Information about data sources used for non-OECD countries is available at www.oecd.org/health/healthataglance.
  17. 17. READER’S GUIDE HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 201320 Population figures The population figures presented in Annex A and used to calculate rates per capita throughout this publication come from the OECD Historical Population Data and Projections (as of end of May 2013), and refer to mid-year estimates. Population estimates are subject to revision, so they may differ from the latest population figures released by the national statistical offices of OECD member countries. Note that some countries such as France, the United Kingdom and the United States have overseas colonies, protectorates or territories. These populations are generally excluded. The calculation of GDP per capita and other economic measures may, however, be based on a different population in these countries, depending on the data coverage. OECD country ISO codes Emerging country ISO codes Australia AUS Japan JPN Austria AUT Korea KOR Belgium BEL Luxembourg LUX Canada CAN Mexico MEX Chile CHL Netherlands NLD Czech Republic CZE New Zealand NZL Denmark DNK Norway NOR Estonia EST Poland POL Finland FIN Portugal PRT France FRA Slovak Republic SVK Germany DEU Slovenia SVN Greece GRC Spain ESP Hungary HUN Sweden SWE Iceland ISL Switzerland CHE Ireland IRL Turkey TUR Israel ISR United Kingdom GBR Italy ITA United States USA Brazil BRA Indonesia IDN China CHN Russian Federation RUS India IND South Africa ZAF
  18. 18. HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 2013 23 1. HEALTH STATUS 1.1. Life expectancy at birth 1.2. Life expectancy by sex and education level 1.3. Mortality from cardiovascular diseases 1.4. Mortality from cancer 1.5. Mortality from transport accidents 1.6. Suicide 1.7. Infant mortality 1.8. Infant health: Low birth weight 1.9. Perceived health status 1.10. Diabetes prevalence and incidence The statistical data for Israel are supplied by and under the responsibility of the relevant Israeli authorities. The use of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements in the West Bank under the terms of international law.
  19. 19. HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 201324 1. HEALTH STATUS 1.1. Life expectancy at birth Life expectancy has increased greatly over the past few decades in all OECD countries and many emerging econo- mies. Improvement in living conditions, a reduction of cer- tain risk factors (e.g., smoking rates) and progress in health care are the main factors explaining increased longevity. For the first time in history, in 2011, life expectancy on aver- age across OECD countries exceeded 80 years, an increase of ten years since 1970 (Figure 1.1.1). Switzerland, Japan and Italy lead a large group of over two-thirds of OECD countries in which life expectancy at birth now exceeds 80 years. A second group, including the United States, Chile and a number of central and eastern European countries, have a life expectancy between 75 and 80 years. Among OECD countries life expectancy was lowest in Mexico and Turkey. While life expectancy in Turkey has increased rap- idly and steadily over the past four decades, the increase in Mexico has slowed down markedly since 2000. Emerging countries such as Brazil, China, Indonesia and India have also achieved large gains in longevity over the past decades, with life expectancy in these countries con- verging rapidly towards the OECD average. There has been much less progress in South Africa (due mainly to the epi- demic of HIV/AIDS) and the Russian Federation (due mainly to the impact of the economic transition in the 1990s and the rise in risky behaviors among men). In the United States, the gains in life expectancy since 1970 have also been much more modest than in most other OECD countries. While life expectancy in the United States used to be one year above the OECD average in 1970, it is now more than one year below the average. Many possible explanations have been suggested for these lower gains in life expectancy, including: 1) the highly fragmented nature of the US health system, with relatively few resources devoted to public health and primary care, and a large share of the population uninsured; 2) health-related behav- iours, including higher calorie consumption per capita and obesity rates, higher consumption of prescription and ille- gal drugs, higher deaths from road traffic accidents and higher homicide rates; and 3) adverse socio-economic con- ditions affecting a large segment of the US population, with higher rates of poverty and income inequality than in most other OECD countries (National Research Council and Insti- tute of Medicine, 2013). Higher national income (as measured by GDP per capita) is generally associated with higher life expectancy at birth, although the relationship is less pronounced at the highest levels of national income (Figure 1.1.2). There are also nota- ble differences in life expectancy between countries with similar income per capita. For example, Japan and Italy have higher, and the United States and the Russian Federation have lower life expectancies than would be pre- dicted by their GDP per capita alone. Figure 1.1.3 shows the relationship between life expectancy at birth and health expenditure per capita across OECD countries and emerging countries. Higher health spending per capita is generally associated with higher life expec- tancy at birth, although this relationship tends to be less pronounced in countries with the highest health spending per capita. Japan, Italy and Spain stand out as having rela- tively high life expectancies, and the United States and the Russian Federation relatively low life expectancies, given their levels of health spending. Many other factors, beyond national income and total health spending, affect life expectancy and explain varia- tions across countries. Definition and comparability Life expectancy at birth measures how long, on aver- age, people would live based on a given set of age- specific death rates. However, the actual age-specific death rates of any particular birth cohort cannot be known in advance. If age-specific death rates are fall- ing (as has been the case over the past decades), actual life spans will be higher than life expectancy calculated with current death rates. The methodology used to calculate life expectancy can vary slightly between countries. This can change a country’s estimates by a fraction of a year. Life expectancy at birth for the total population is calculated by the OECD Secretariat for all OECD coun- tries, using the unweighted average of life expectancy of men and women.
  20. 20. 1. HEALTH STATUS 1.1. Life expectancy at birth HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 2013 25 1.1.2. Life expectancy at birth and GDP per capita, 2011 (or nearest year) Source: OECD Health Statistics 2013, http://dx.doi.org/10.1787/health-data-en. 1 2 http://dx.doi.org/10.1787/888932916021 1.1.3. Life expectancy at birth and health spending per capita, 2011 (or nearest year) Source: OECD Health Statistics 2013, http://dx.doi.org/10.1787/health-data-en; World Bank for non-OECD countries. 1 2 http://dx.doi.org/10.1787/888932916040 1.1.1. Life expectancy at birth, 1970 and 2011 (or nearest year) Source: OECD Health Statistics 2013, http://dx.doi.org/10.1787/health-data-en; World Bank for non-OECD countries. 1 2 http://dx.doi.org/10.1787/888932916002 40 50 60 70 80 90 82.8 82.7 82.7 82.4 82.4 82.2 82.0 81.9 81.8 81.4 81.3 81.2 81.1 81.1 81.1 81.1 81.0 80.8 80.8 80.8 80.6 80.6 80.5 80.1 80.1 79.9 78.7 78.0 76.9 76.3 76.1 75.0 74.6 74.2 73.5 73.4 69.3 69.0 65.5 52.6 78.3 Years SwitzerlandJapan ItalySpainIcelandFrance AustraliaSwedenIsraelNorway Netherlands New Zealand Luxem bourgAustria United Kingdom KoreaCanada Germ anyGreecePortugalFinlandIrelandBelgiumSloveniaOECD34 Denm ark United States Chile Czech Rep.PolandEstonia SlovakRep. HungaryTurkeyM exicoChinaBrazil Indonesia Russian Fed.India South Africa 2011 1970 0 10 000 20 000 30 000 40 000 50 000 60 000 70 000 NOR CHL POL MEX SVK EST HUNTUR CHN BRA IDN RUS IND R² = 0.58 AUS AUT BEL CAN CZE DNK FIN FRA DEU GRC ISL IRL ISR ITA JPN KOR NLDNZL PRT SVN ESP SWE CHE GBR USA 65 70 75 80 85 GDP per capita (USD PPP) Life expectancy in years R² = 0.51 65 70 75 80 85 0 2 000 4 000 6 000 8 000 10 000 AUS AUT BEL BRA CAN CHL CHN CZE DNK EST FIN FRA DEUGRC HUN ISL IND IDN IRL ISR ITA JPN KOR LUX MEX NLD NZL NOR POL PRT RUS SVK SVN ESP SWE CHE TUR GBR USA Health spending per capita (USD PPP) Life expectancy in years
  21. 21. HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 201326 1. HEALTH STATUS 1.2. Life expectancy by sex and education level There remain large gaps in life expectancy between women and men in all OECD countries. On average across OECD countries, life expectancy at birth for women reached 82.8 years in 2011, compared with 77.3 years for men, a gap of 5.5 years (Figure 1.2.1). The gender gap in life expectancy increased substantially in many OECD countries during the 1970s and early 1980s to reach a peak of almost seven years in the mid-1980s, but it has narrowed during the past 25 years, reflecting higher gains in life expectancy among men than among women. This can be attributed at least partly to the narrowing of differences in risk-increasing behaviours, such as smoking, accompanied by sharp reductions in mortality rates from cardiovascular diseases among men. In 2011, the life expectancy for women in OECD countries varied from a low of 77 years in Turkey and Mexico to a high of nearly 86 years in Japan and France. Life expec- tancy for men ranged from 71 years in Estonia, Hungary and Mexico, to over 80 years in Iceland, Switzerland and Italy. The life expectancy for both women and men is much shorter in South Africa (at only 53 and 52 years respectively in 2011), due largely to the HIV/AIDS epidemic. In the United States, the life expectancy for both women and men is now slightly shorter than the OECD average, and the gap with leading countries has been widening. The life expectancy for US men in 2011 was 4.2 years shorter than in Switzerland (up from less than three years in 1970); for US women, it was 4.8 years shorter than in Japan in 2011 (there was no gap in 1970). Possible explana- tions for this slower progress are provided in Indicator 1.1. Among OECD countries, the gender gap in life expectancy is relatively narrow in Iceland, Israel, New Zealand, the Netherlands and Sweden (a gap of less than four years), but much larger in Estonia (more than ten years), Hungary, the Slovak Republic and Poland (7.5 years or more), and France (seven years). In the Russian Federation, the gender gap in life expectancy reached almost 12 years in 2011. This large gap in life expectancy between Russian men and women can be explained to a large extent by higher smoking rates and alcohol consumption, and higher death rates from road traffic accidents, homicides and suicides (OECD, 2012c). Life expectancy in OECD countries varies not only by gen- der, but also by socio-economic status as measured for instance by education level (Figure 1.2.2). Higher education level not only provides the means to improve the socio- economic conditions in which people live and work, but may also promote the adoption of more healthy lifestyles and facilitate access to appropriate health care. On average among 14 OECD countries for which data are available, peo- ple with the highest level of education can expect to live six years more than people with the lowest level of education at age 30 (53 years versus 47 years). These differences in life expectancy by education level are particularly pro- nounced for men, with a gap of almost eight years on aver- age. They are particularly large in central and eastern European countries (Czech Republic, Estonia, Hungary, Poland and Slovenia), where the life expectancy gap between higher and lower educated men reaches more than ten years. Differences in Portugal, Sweden, Switzerland and Italy are less pronounced, although not negligible. Definition and comparability Life expectancy at birth measures how long, on aver- age, people would live based on a given set of age- specific death rates. However, the actual age-specific death rates of any particular birth cohort cannot be known in advance. If age-specific death rates are fall- ing (as has been the case over the past decades), actual life spans will be higher than life expectancy calculated with current death rates. The methodology used to calculate life expectancy can vary slightly between countries. This can change a country’s estimates by a fraction of a year. To calculate life expectancies by education level, detailed data on deaths by sex, age and education level are needed. However, not all countries have information on education as part of their deaths data. Data linkage to another source (e.g. a census) which does have information on education may be required (Corsini, 2010).
  22. 22. 1. HEALTH STATUS 1.2. Life expectancy by sex and education level HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 2013 27 1.2.1. Life expectancy at birth by sex, 2011 (or nearest year) Note: Countries are ranked in descending order of life expectancy for the whole population. Source: OECD Health Statistics 2013, http://dx.doi.org/10.1787/health-data-en; World Bank for non-OECD countries. 1 2 http://dx.doi.org/10.1787/888932916059 1.2.2. Gap in life expectancy at age 30 by sex and education level, 2010 (or nearest year) Note: The figures show the gap in the expected years of life remaining at age 30 between adults with the highest level (“tertiary education”) and the lowest level (“below upper secondary education”) of education. Source: Eurostat database complemented with national data for Austria, Netherlands and Switzerland. 1 2 http://dx.doi.org/10.1787/888932916078 40 50 60 70 80 90 Years Women Men SwitzerlandJapan ItalySpainIcelandFrance AustraliaSwedenIsraelNorway Netherlands New Zealand Luxem bourgAustria United Kingdom KoreaCanada Germ anyGreecePortugalFinlandIrelandBelgiumSloveniaOECD34 Denm ark United States Chile Czech Rep.PolandEstonia SlovakRep. HungaryTurkeyM exicoChinaBrazil Indonesia Russian Fed.India South Africa 05101520 0 2 4 6 8 10 2.9 3.9 4.4 5.0 5.2 5.4 5.7 5.7 5.8 7.8 10.4 12.0 13.1 13.5 16.8 1.0 2.9 2.2 2.8 4.1 2.6 3.8 3.2 3.3 3.8 4.4 4.8 5.4 8.5 4.6 Gap in yearsGap in years WomenMen Netherlands (2009) Italy (2009) Switzerland (2007) Sweden Portugal Slovenia OECD14 Norway Finland Denmark Austria (2007) Czech Rep. Estonia Hungary Poland
  23. 23. HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 201328 1. HEALTH STATUS 1.3. Mortality from cardiovascular diseases Cardiovascular diseases are the main cause of mortality in most OECD countries, and accounted for 33% of all deaths in 2011. They cover a range of diseases related to the circu- latory system, including ischemic heart disease (often referred to as heart attack) and cerebrovascular diseases such as stroke. Ischemic heart disease (IHD) is caused by the accumulation of fatty deposits lining the inner wall of a coronary artery, restricting blood flow to the heart. IHD alone was responsi- ble for 12% of all deaths in OECD countries in 2011. Mortality from IHD varies considerably, however, across countries (Figure 1.3.1). Central and eastern European countries report the highest IHD mortality rates; Japan, Korea and France are the countries with the lowest rates. Across OECD countries, IHD mortality rates in 2011 were 90% higher for men than women. IHD mortality rates have declined in nearly all OECD coun- tries, with an average fall of 40% since 1990. The decline has been most remarkable in Denmark, the Netherlands, and Norway, where rates fell by two-thirds or more. Declining tobacco consumption contributed significantly to reducing the incidence of IHD, and consequently to reducing mortality rates. Improvements in medical care have also contributed to reduced mortality rates (see Indicator 4.6 “Cardiac proce- dures” and 5.3 “Mortality following acute myocardial infarction”). The Slovak Republic and Mexico as well as Korea have witnessed a rise in IHD mortality rates. The increase was particularly large in Korea; however IHD mortality remains low in Korea and has started to fall after peaking in 2006. The initial rise has been attributed to changes in lifestyle and dietary patterns as well as environmental factors at the time of birth, with people born between 1940 and 1950 fac- ing higher relative risks (OECD, 2012b; Juhn et al., 2011; Lee et al., 2012). Cerebrovascular disease was the underlying cause for about 8% of all deaths in OECD countries in 2011. Cerebro- vascular diseases refer to a group of diseases that relate to problems with the blood vessels that supply the brain. Common types of cerebrovascular disease include ischemic stroke, which develops when the brain’s blood supply is blocked or interrupted, and haemorrhagic stroke which occurs when blood leaks from blood vessels onto the surface of the brain. In addition to being an important cause of mortality, the disability burden from stroke and other cerebrovascular diseases is also substantial (Murray et al., 2013). There are large variations in cerebrovascular disease mortality rates across countries (Figure 1.3.2). Hungary and the Slovak Republic report a cerebrovascular mortality that is more than three times higher than that of Switzerland and France. Many of the central and eastern European countries including the Czech Republic and Estonia have high mortality rates for both IHD and cerebrovascular disease. The high prevalence of risk factors common to both diseases (e.g. smoking and high blood pressure) helps explain this link. Since 1990, cerebrovascular disease mortality has decreased in all OECD countries, although only marginally in Poland and the Slovak Republic. On average, the mortal- ity burden from cerebrovascular disease has been halved across OECD countries. In Estonia, Luxembourg, Portugal and Spain, the rates have been cut by at least two-thirds. As with IHD, the reduction in mortality from cerebrovascular disease can be attributed at least partly to a reduction in risk factors as well as improvements in medical treatments (see Indicator 5.4 “Mortality following stroke”). Definition and comparability Mortality rates are based on numbers of deaths regis- tered in a country in a year divided by the size of the corresponding population. The rates have been directly age-standardised to the 2010 OECD popula- tion to remove variations arising from differences in age structures across countries and over time. The source is the WHO Mortality Database. Deaths from ischemic heart disease are classified to ICD-10 codes I20-I25, and cerebrovascular disease to I60-I69. Mathers et al. (2005) have provided a general assessment of the coverage, completeness and reli- ability of data on causes of death.
  24. 24. 1. HEALTH STATUS 1.3. Mortality from cardiovascular diseases HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 2013 29 1.3.1. Ischemic heart disease mortality, 2011 and change between 1990 and 2011 (or nearest year) Source: OECD Health Statistics 2013, http://dx.doi.org/10.1787/health-data-en. 1 2 http://dx.doi.org/10.1787/888932916097 1.3.2. Cerebrovascular disease mortality, 2011 and change between 1990 and 2011 (or nearest year) Source: OECD Health Statistics 2013, http://dx.doi.org/10.1787/health-data-en. 1 2 http://dx.doi.org/10.1787/888932916116 -100 -75 -50 -25 0 25 50 750100200300400500 39 42 48 52 56 61 70 72 75 80 84 85 89 90 94 98 108 113 115 122 123 127 128 133 136 142 147 148 172 260 265 309 404 -32 60 -47 -55 -69 -41 -54 -55 -77 -38 -64 -35 -38 -45 -66 -47 -64 -54 -62 -48 -42 -55 -50 -13 -46 -59 -37 18 -49 -49 -41 -59 -6 9 68 Change in % over the periodAge-standardised rates per 100 000 population Change 1990-20112011 Germany OECD33 Sweden United States Switzerland Norway Slovenia United Kingdom Finland Czech Rep. Estonia Slovak Rep. Hungary Poland Iceland Ireland Austria Mexico New Zealand Chile Denmark Belgium Israel Greece Italy Canada Australia Spain Luxembourg Japan Korea France Portugal Netherlands 050100150200 -100 -75 -50 -25 0 25 50 41 41 42 43 43 48 48 50 51 53 55 57 58 59 60 61 61 61 67 67 67 68 69 70 80 81 83 92 97 99 106 112 124 137 -56 -53 -59 -46 -43 -69 -55 -65 -55 -62 -50 -49 -57 -71 -41 -54 -56 -44 -21 -44 -56 -51 -51 -52 -54 -39 -74 -51 -71 -2 -66 -48 -52 -2 Change in % over the periodAge-standardised rates per 100 000 population Change 1990-20112011 Portugal Poland Czech Rep. Greece Hungary Italy Korea Slovenia Slovak Rep. Chile Estonia Iceland Japan Sweden Mexico United Kingdom OECD33 New Zealand Finland Spain Australia Denmark Germany Belgium Norway Luxembourg Ireland Canada United States Austria Netherlands Switzerland France Israel
  25. 25. HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 201330 1. HEALTH STATUS 1.4. Mortality from cancer Cancer accounts for over one-fourth of all deaths in OECD countries and, after diseases of the circulatory system, it is the second leading cause of death. The proportion of deaths that are due to cancer has increased over time, and in countries such as Canada, Denmark, France, Japan and the Netherlands it has become the number one cause of death. This rise reflects the fact that mortality from other causes, particularly circulatory diseases, has been declin- ing at a faster pace than the mortality rate for cancer. There are more than 100 different types of cancers, with most named for the organ in which they start. Cancer occurs when abnormal cells divide without control and are able to invade other tissues. For a large number of cancer types, the risk of developing the disease rises with age. While genetics is a risk factor, only about 5% to 10% of all cancers are inherited. Modifiable risk factors such as smok- ing, obesity, exercise, and excess sun exposure, as well as environmental exposures, explain as much as 90-95% of all cancer cases (Anand et al., 2008). Prevention, early detec- tion and treatment remain at the forefront in the battle to reduce the burden of cancer. In 2011, the average cancer mortality rate across OECD countries was 211 per 100 000 population. Mortality was lowest in Mexico, Brazil and Finland, with rates less than 180 per 100 000 population. Central and eastern European coun- tries such as Hungary, Slovenia and the Slovak Republic as well Denmark bear the biggest cancer burden with mortality rates in excess of 240 per 100 000 population (Figure 1.4.1). Cancer mortality rates are persistently higher for men than for women in all countries (Figure 1.4.1). The gender gap was particularly wide in Korea, Spain and Estonia, along with the Slovak Republic, Japan and France; with mortality rates among men more than twice those for women. This gender gap can be explained partly by the greater preva- lence of risk factors among men, notably smoking rates. Among men, lung cancer imposes the highest mortality burden, accounting for 23% of all cancer-related deaths. In Belgium and Greece, this percentage was in excess of 30%. For women, lung cancer accounted for 16% of all cancer- related deaths. In many countries, lung cancer mortality rates for men have decreased over the last 20 years, whereas the opposite trend can be observed for women. These conflicting trends are, to a large degree, explained by the large number of females who started smoking several decades later than males (Ahmedin et al., 2011). Mortality, survival and screening rates for cervical, breast and colorectal cancer are discussed further in Chapter 5. In most OECD countries, cancer-related death rates have fallen since 1990. On average, cancer-related mortality rates fell by nearly 15% between 1990 and 2011 (Figure 1.4.2). Substantial declines in mortality from stom- ach, colorectal, breast and cervical cancer for women, as well as prostate and lung cancer for men contributed to this reduction. However, these gains were partially offset by increases in the number of deaths due to cancer of the pan- creas and liver for both sexes as well as lung cancer for women. In the case of Brazil, Korea, South Africa and Slovenia, how- ever, cancer-related mortality increased over this period (Figure 1.4.2). In all other countries, mortality rates fell, but there is substantial variation between countries in the rate of decline. Mortality rates fell by a modest 2% to 5% in Greece, the Slovak Republic and Estonia, but by more than 25% in Switzerland, Luxembourg and the Czech Republic. Definition and comparability Mortality rates are based on numbers of deaths regis- tered in a country in a year divided by the size of the corresponding population. The rates have been directly age-standardised to the 2010 OECD popula- tion to remove variations arising from differences in age structures across countries and over time. The source is the WHO Mortality Database. Deaths from all cancers are classified to ICD-10 codes C00-C97. Mathers et al. (2005) have provided a general assessment of the coverage, completeness and reli- ability of data on causes of death.
  26. 26. 1. HEALTH STATUS 1.4. Mortality from cancer HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 2013 31 1.4.1. All cancer mortality rates, total and by gender, 2011 (or nearest year) Source: OECD Health Statistics 2013, http://dx.doi.org/10.1787/health-data-en. 1 2 http://dx.doi.org/10.1787/888932916135 1.4.2. Change in all cancer mortality rates, 1990-2011 (or nearest year) Source: OECD Health Statistics 2013, http://dx.doi.org/10.1787/health-data-en. 1 2 http://dx.doi.org/10.1787/888932916154 0 50 100 150 200 250 300 350 400 450 Women Men Total Age-standardised rates per 100 000 population M exico BrazilFinland Switzerland Japan KoreaSweden IsraelSpain United StatesPortugalGreeceAustraliaAustria Luxem bourgGerm any Chile ItalyNorwayIcelandOECD33 Russian Fed.FranceCanadaBelgium New ZealandIreland United Kingdom NetherlandsEstoniaPoland Czech Rep. Denm ark SlovakRep.SloveniaHungary -40 -30 -20 -10 0 10 20 -28 -27 -25 -23 -22 -22 -21 -20 -20 -20 -20 -19 -18 -17 -17 -17 -16 -16 -15 -14 -13 -13 -12 -12 -12 -11 -10 -10 -6 -6 -4 -4 -3 0 3 6 11 Change in % over the period Switzerland Luxem bourg Czech Rep. United StatesBelgiumAustriaIrelandGerm any New ZealandFinland Italy United KingdomAustraliaDenm arkCanadaFranceIceland Russian Fed. NetherlandsOECD33 SpainM exicoSwedenHungaryJapan ChileNorway IsraelPolandPortugalEstonia SlovakRep.GreeceSlovenia South AfricaKorea Brazil
  27. 27. HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 201332 1. HEALTH STATUS 1.5. Mortality from transport accidents Worldwide, an estimated 1.3 million people are killed in transport accidents each year, most of which are due to road traffic accidents. Globally, road transport accidents account for 0.5% of deaths among women aged 15-45 but over 10% for men in this age group (Lozano et al., 2012). In OECD countries, 107 000 lives were lost due to transport accidents in 2011. Seventy-four per cent of these fatalities occurred among men. The largest number of road transport accidents occurs among younger age groups with the risk of dying due to a road accident peaking at ages 15-24 (Walls et al., 2012; OECD/ITF, 2013). The average OECD mortality rate due to transport accidents was 7.7 per 100 000 population in 2011 (Figure 1.5.1). There is great dispersion between countries with transport acci- dents claiming more than five times as many lives per 100 000 population in Mexico compared to Sweden. Fatali- ties were in excess of 14 deaths per 100 000 population in Mexico and Chile, and were even higher in other large emerging countries such as Brazil and the Russian Federation. They were lowest in Sweden, the United Kingdom and Denmark with four deaths or less per 100 000 population. Most fatal traffic injuries occur in passenger vehicles, although other road users also face substantial risks. In Korea, Israel, Japan and Korea, pedestrians account for over one third of all road user fatalities. Motorcyclists account for over 25% of road transport accident deaths in Greece, Italy and France (OECD/ITF, 2013). Deaths due to transport accidents have decreased in almost all countries over the last few decades. Since 1990, the average OECD mortality rate due to transport accidents has fallen by more than half (Figure 1.5.2). Spain, Estonia and Iceland have slashed their mortality rates by more than 75% over the 20-year period. These gains are even more impressive when considering the increase in the number of vehicle kilometres travelled over this period (OECD/ITF, 2013). Chile is the only country where mortality rates due to transport accidents have increased, and are now at a similar level to countries such as Korea, the United States and Greece. At the start of the 1990s, Chile’s mortal- ity rate was comparatively low and its rise in road traffic fatalities may be associated with its rapid economic growth during this period (Nghiem et al., 2013). Road safety for car occupants has increased greatly over the past decades in many countries through improvements of road systems, education and prevention campaigns as well as vehicle design. In addition, the adoption of new laws and regulations and the enforcement of these laws to improve compliance with speed limits, seatbelt use and drink-driving rules, have had a major impact on reducing the burden of road transport accidents. More gains can be made if countries can further improve seatbelt use (OECD/ ITF, 2013). Declines in mortality rates for vulnerable road users such as pedestrians, cyclists and motorcyclists were substan- tially less than those for car occupants. Between 2000 and 2010, fatalities among motorcyclists fell by only 14% across the OECD, with some countries such as the United States, Poland and Finland witnessing significant increases among this class of road users (although there have been reports of recent reductions in deaths from motorcycle accidents in Finland since 2010). In some countries hard-hit by the economic recession, the downward trend has accelerated after 2008. Preliminary data suggests that the rate of decline between 2009 and 2012 in Greece and Ireland is even greater than the long- term average observed in those countries. One possible explanation for this is that the economic crisis has reduced reliance on motor vehicle use. However, this impact is likely to be short-lived and over the longer term, effective road safety policies will remain the primary contributor to reduced mortality (OECD/ITF, 2011). Definition and comparability Mortality rates are based on numbers of deaths regis- tered in a country in a year divided by the size of the corresponding population. The rates have been directly age-standardised to the 2010 OECD popula- tion to remove variations arising from differences in age structures across countries and over time. The source is the WHO Mortality Database. Deaths from transport accidents are classified to ICD-10 codes V01-V89. Mathers et al. (2005) have pro- vided a general assessment of the coverage, com- pleteness and reliability of data on causes of death.
  28. 28. 1. HEALTH STATUS 1.5. Mortality from transport accidents HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 2013 33 1.5.1. Transport accident mortality rates, 2011 (or nearest year) Source: OECD Health Statistics 2013, http://dx.doi.org/10.1787/health-data-en; and Ministry of Health for New Zealand. 1 2 http://dx.doi.org/10.1787/888932916173 1.5.2. Trends in transport accident mortality rates, selected OECD countries, 1990-2011 Source: OECD Health Statistics 2013, http://dx.doi.org/10.1787/health-data-en. 1 2 http://dx.doi.org/10.1787/888932916192 0 5 10 15 20 25 30 3.2 3.6 4.0 4.2 4.3 4.3 4.4 4.5 4.7 4.9 5.1 5.6 5.9 6.2 6.3 6.5 6.8 7.1 7.3 7.6 7.8 7.9 8.2 8.7 8.7 8.8 9.3 9.4 12.2 12.3 12.4 13.8 14.1 14.4 17.5 19.2 24.9 Age-standardised rates per 100 000 population Sweden United KingdomDenm arkIceland NetherlandsIreland SwitzerlandJapanNorway SpainGerm any Luxem bourg IsraelAustriaFinland New ZealandAustraliaFrance ItalyOECD33CanadaSlovenia Czech Rep.PortugalHungaryEstonia SlovakRep.BelgiumPolandGreece United States Korea South Africa ChileM exico Russian Fed.Brazil 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 0 5 10 15 20 25 0 5 10 15 20 25 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 United States Canada OECD Chile Mexico Ireland France OECD Germany Spain Greece Age-standardised rates per 100 000 population Age-standardised rates per 100 000 population
  29. 29. HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 201334 1. HEALTH STATUS 1.6. Suicide Suicide is a significant cause of death in many OECD coun- tries, and accounted for over 150 000 deaths in 2011. There is a complex set of reasons why some people choose to attempt or commit suicide, with multiple risk factors that can predispose a person to attempt to take their own life. Over 90% of people who have attempted or committed sui- cide have been diagnosed with psychiatric disorders such as severe depression, bipolar disorder and schizophrenia (Nock et al., 2008). The social context in which an individual lives is also important. Low income, alcohol and drug abuse, unemployment and unmarried status are all associ- ated with higher rates of suicide (Qin et al., 2003; Crump et al., 2013). Figure 1.6.1 shows that suicide rates were lowest in Greece, Turkey, Mexico, Brazil and Italy, at six or fewer deaths per 100 000 population. In Korea, Hungary, the Russian Federation and Japan, on the other hand, suicide is responsible for more than 20 deaths per 100 000 population. There is a ten- fold difference between Korea and Greece, the two coun- tries with the highest and lowest suicide rates. However, the number of suicides in certain countries may be under- reported because of the stigma that is associated with the act, or because of data issues associated with reporting cri- teria (see “Definition and comparability”). Death rates from suicide are four times greater for men than for women across OECD countries. In Greece and Poland, men are at least seven times more likely to commit suicide than women. The gender gap in those two countries has widened in recent years. While in Luxembourg and the Netherlands the gender gap is smaller, male suicide rates are still twice those of females. Since 1990, suicide rates have decreased by more than 20% across OECD countries, with pronounced declines of over 40% in some countries such as Hungary (Figure 1.6.2). In Estonia, rates fell by nearly 50% over the 20-year period, but not before rising substantially in the mid-1990s. Death rates from suicides have increased in countries such as Korea and Japan. In Japan, there was a sharp rise in the mid-to-late 1990s, coinciding with the Asian Financial Crisis; but rates have remained stable since then. Suicide rates also rose sharply at this time in Korea and, unlike in Japan, have continued to increase. It is now the fourth lead- ing cause of death in Korea (Jeon, 2011). Mental health ser- vices in Korea lag behind those of other countries with fragmented support, focused largely around institutions, with insufficient or ineffective support provided to those who remain in the community. Further efforts are also needed to remove the stigma associated with seeking care (OECD, forthcoming). Previous studies have shown a strong link between adverse economic conditions and higher levels of suicide (Ceccherini-Nelli et al., 2011; Classen and Dunn, 2012; Zivin et al., 2011). Figure 1.6.2 shows suicide rates for a number of countries that have been hard hit by the recent economic crisis. Suicide rates rose slightly at the start of the eco- nomic crisis in a number of countries such as Ireland but more recent data suggest that this trend did not persist. In Greece, overall suicide rates were stable in 2009 and 2010, despite worsening economic conditions. There is a need for countries to continue monitoring developments closely in order to be able to respond quickly, including monitoring high-risk populations such as the unemployed and those with psychiatric disorders (see Indicator 5.8 for further information). Definition and comparability The World Health Organization defines suicide as an act deliberately initiated and performed by a person in the full knowledge or expectation of its fatal out- come. Comparability of data between countries is affected by a number of reporting criteria, including how a person’s intention of killing themselves is ascertained, who is responsible for completing the death certificate, whether a forensic investigation is carried out, and the provisions for confidentiality of the cause of death. Caution is required therefore in interpreting variations across countries. Mortality rates are based on numbers of deaths regis- tered in a country in a year divided by the size of the corresponding population. The rates have been directly age-standardised to the 2010 OECD popula- tion to remove variations arising from differences in age structures across countries and over time. The source is the WHO Mortality Database. Deaths from suicide are classified to ICD-10 codes X60-X84. Mathers et al. (2005) have provided a general assess- ment of the coverage, completeness and reliability of data on causes of death.
  30. 30. 1. HEALTH STATUS 1.6. Suicide HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 2013 35 1.6.1. Suicide mortality rates, 2011 (or nearest year) Source: OECD Health Statistics 2013, http://dx.doi.org/10.1787/health-data-en. 1 2 http://dx.doi.org/10.1787/888932916211 1.6.2. Trends in suicide rates, selected OECD countries, 1990-2011 Source: OECD Health Statistics 2013, http://dx.doi.org/10.1787/health-data-en. 1 2 http://dx.doi.org/10.1787/888932916230 0 5 10 15 20 25 30 35 3.1 4.3 4.8 5.4 5.8 6.2 6.7 7.4 8.5 9.5 10.1 10.1 10.4 10.8 11.0 11.1 11.3 11.7 11.8 11.9 12.0 12.1 12.4 12.5 13.3 14.0 14.3 15.1 15.3 16.2 16.4 17.9 18.6 20.9 22.5 22.8 33.3 Age-standardised rates per 100 000 population GreeceTurkeyM exico Brazil Italy Spain United Kingdom IsraelPortugal NetherlandsAustraliaDenm ark Luxem bourgGerm anyIrelandCanada SlovakRep.SwedenIceland Switzerland New ZealandNorwayOECD34 United States ChileAustria Czech Rep.PolandEstoniaFranceFinlandBelgiumSloveniaJapan Russian Fed.HungaryKorea 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 0 10 20 30 40 50 Japan Estonia Greece Korea Age-standardised rates per 100 000 population Spain Hungary OECD Ireland
  31. 31. HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 201336 1. HEALTH STATUS 1.7. Infant mortality Infant mortality, the rate at which babies and children of less than one year of age die, reflects the effect of economic and social conditions on the health of mothers and new- borns, the social environment, individual lifestyles as well as the characteristics and effectiveness of health systems. In most OECD countries, infant mortality is low and there is little difference in rates (Figure 1.7.1). In 2011, the average in OECD countries was just over four deaths per 1 000 live births, with rates being the lowest in Nordic countries (Iceland, Sweden, Finland, Norway), Japan and Estonia. A small group of OECD countries still have relatively high rates of infant mortality (Mexico, Turkey and Chile), although in these three countries infant mortality rates have come down rapidly over the past few decades (Figure 1.7.2). In some large non-member countries (India, South Africa and Indonesia), infant mortality rates remain above 20 deaths per 1 000 live births. In India, nearly one-in- twenty children die before their first birthday, although the rates have fallen sharply over the past few decades. Infant mortality rates have also been reduced greatly in Indonesia. In OECD countries, around two-thirds of the deaths that occur during the first year of life are neonatal deaths (i.e., during the first four weeks). Birth defects, prematurity and other conditions arising during pregnancy are the principal factors contributing to neonatal mortality in developed countries. With an increasing number of women deferring childbearing and a rise in multiple births linked with fertil- ity treatments, the number of pre-term births has tended to increase (see Indicator 1.8 “Infant health: Low birth weight”). In a number of higher-income countries, this has contributed to a levelling-off of the downward trend in infant mortality rates over the past few years. For deaths beyond a month (post-neonatal mortality), there tends to be a greater range of causes – the most common being SIDS (sudden infant death syndrome), birth defects, infections and accidents. All OECD countries have achieved remarkable progress in reducing infant mortality rates from the levels of 1970, when the average was approaching 30 deaths per 1 000 live births, to the current average of just over four. Besides Mexico, Chile and Turkey where the rates have converged rapidly towards the OECD average (Figure 1.7.2), Portugal and Korea have also achieved large reductions in infant mortality rates, moving from countries that were well above the OECD average in 1970 to being well below the OECD average in 2011. By contrast, in the United States, the reduction in infant mortality has been slower than in most other OECD coun- tries. In 1970, the US rate was well below the OECD average, but it is now well above (Figure 1.7.1). Part of the explana- tion for the relatively high infant mortality rates in the United States is due to a more complete registration of very premature or low birth weight babies than in other coun- tries (see box on “Definition and comparability”). However, this cannot explain why the post-neonatal mortality rate (deaths after one month) is also greater in the United States than in most other OECD countries. There are large differ- ences in infant mortality rates among racial groups in the United States, with black (or African-American) women more likely to give birth to low birth weight infants, and with an infant mortality rate more than double that for white women (11.6 vs. 5.2 in 2010) (NCHS, 2013). Many studies use infant mortality as a health outcome to examine the effect of a variety of medical and non-medical determinants of health (e.g., OECD, 2010a). Although most analyses show that higher health spending tends to be associated with lower infant mortality, the fact that some countries with a high level of health expenditure do not exhibit low levels of infant mortality suggests that more health spending is not necessarily required to obtain better results (Retzlaff-Roberts et al., 2004). A body of research also suggests that many factors beyond the quality and efficiency of the health system, such as income inequality, the socio-economic environment and individual lifestyles, influence infant mortality rates (Kiely et al., 1995). Definition and comparability The infant mortality rate is the number of deaths of children under one year of age, expressed per 1 000 live births. Neonatal mortality refers to the death of children during the first four weeks of life. Post-neonatal mortality refers to deaths occurring between the second and the twelfth months of life. Some of the international variation in infant and neo- natal mortality rates is due to variations among coun- tries in registering practices for premature infants. The United States and Canada are two countries which register a much higher proportion of babies weighing less than 500 g, with low odds of survival, resulting in higher reported infant mortality (Joseph et al., 2012). In Europe, several countries apply a min- imum gestational age of 22 weeks (or a birth weight threshold of 500g) for babies to be registered as live births (Euro-Peristat, 2013).
  32. 32. 1. HEALTH STATUS 1.7. Infant mortality HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 2013 37 1.7.1. Infant mortality rates, 2011 (or nearest year) 1. Three-year average (2009-11). Source: OECD Health Statistics 2013, http://dx.doi.org/10.1787/health-data-en; World Bank for non-OECD countries. 1 2 http://dx.doi.org/10.1787/888932916249 1.7.2. Infant mortality rates, selected OECD countries, 1970-2011 Source: OECD Health Statistics 2013, http://dx.doi.org/10.1787/health-data-en. 1 2 http://dx.doi.org/10.1787/888932916268 0 10 20 30 40 50 1.6 2.1 2.3 2.4 2.4 2.5 2.7 2.9 3.0 3.1 3.2 3.3 3.4 3.4 3.4 3.5 3.5 3.5 3.6 3.6 3.6 3.6 3.8 3.8 4.1 4.3 4.7 4.9 4.9 4.9 5.5 6.1 7.4 7.7 9.8 12.6 13.6 13.9 24.8 34.6 47.2 Neonatal Post-neonatal Iceland¹SwedenJapanFinlandNorwayEstonia Czech Rep. SloveniaKorea PortugalSpainBelgium Luxem bourg¹Greece ItalyIrelandIsraelFrance Denm ark Germ anyAustria Netherlands Australia SwitzerlandOECD34 United KingdomPolandCanadaHungary SlovakRep. New Zealand United States ChileTurkey Russian Fed.ChinaM exicoBrazil Indonesia South Africa India Deaths per 1 000 live births 1970 1975 1980 1985 1990 1995 2000 2005 2010 0 30 60 90 120 150 Chile Mexico Deaths per 1 000 live births Turkey OECD
  33. 33. HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 201338 1. HEALTH STATUS 1.8. Infant health: Low birth weight Low birth weight – defined as newborns weighing less than 2 500 grams – is an important indicator of infant health because of the close relationship between birth weight and infant morbidity and mortality. There are two categories of low birth weight babies: those occurring as a result of restricted foetal growth and those resulting from pre-term birth. Low birth weight infants have a greater risk of poor health or death, require a longer period of hospitalisation after birth, and are more likely to develop significant dis- abilities (UNICEF and WHO, 2004). Risk factors for low birth weight include maternal smoking and excessive alcohol consumption, poor nutrition, low body mass index, lower socio-economic status, and having had in-vitro fertilisation treatment and multiple births. One in 15 babies born in OECD countries in 2011 – or 6.8% of all births – weighed less than 2 500 grams at birth (Figure 1.8.1). The proportions of low-weight births were lowest in Nordic countries (Iceland, Finland, Sweden, Norway, with the exception of Denmark) and Estonia, with less than 5% of live births defined as low birth weight. Alongside a number of key emerging countries (India, South Africa and Indonesia), Turkey, Greece and Japan have the highest proportions among OECD countries, with rates of low birth weight infants above 9%. Some of these variations across countries may be due to physiological differences in size between populations (Euro-Peristat, 2013). In some emerging countries, the high proportion of low birth weight infants is mainly associated with mater- nal malnutrition before and during pregnancy, poor health and limited access to proper health care during pregnancy. In almost all OECD countries, the proportion of low birth weight infants has increased over the past two decades (Figure 1.8.1, right panel and Figure 1.8.2). There are several reasons for this rise. The number of multiple births, with the increased risks of pre-term births and low birth weight, has risen steadily, partly as a result of the rise in fertility treatments. Other factors which may explain the rise in low birth weight are older age at childbearing, and increases in the use of delivery management techniques such as induc- tion of labour and caesarean delivery, which have increased the survival rates of low birth weight babies. Korea, Spain, Greece, Japan and Portugal have seen large increases of low birth weight babies over the past two decades. In Japan, this increase can be explained by changes in obstetric interventions, in particular the greater use of caesarean sections, along with changes in maternal socio-demographic and behavioural factors (Yorifuji et al., 2012). This contrasts with sharp decreases in Poland and Hungary, although most of the reduction in these two countries occurred in the first half of the 1990s, with little change since then. Comparisons of different population groups within coun- tries indicate that the proportion of low birth weight infants may also be influenced by differences in education level, income and associated living conditions. In the United States, there are marked differences in the propor- tion of low birth weight infants among racial groups, with black infants having a rate almost double that of white infants (13.2% versus 7.1% in 2010) (NCHS, 2013). Similar differences have also been observed among the indigenous and non-indigenous populations in Australia, Mexico and New Zealand, often reflecting the disadvantaged living conditions of many of these mothers. The proportion of low birth weight infants is also much higher among women who smoke than for non-smokers. In the United States, the rate reached 12.0% for cigarette smokers compared with 7.4% for non-smokers in 2010 (NCHS, 2013). Definition and comparability Low birth weight is defined by the World Health Organization (WHO) as the weight of an infant at birth of less than 2 500 grams (5.5 pounds) irrespec- tive of the gestational age of the infant. This thresh- old is based on epidemiological observations regarding the increased risk of death to the infant and serves for international comparative health statistics. The number of low weight births is then expressed as a percentage of total live births.
  34. 34. 1. HEALTH STATUS 1.8. Infant health: Low birth weight HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 2013 39 1.8.1. Low birth weight infants, 2011 and change between 1990 and 2011 (or nearest year) Source: OECD Health Statistics 2013, http://dx.doi.org/10.1787/health-data-en; World Bank and WHO for key partners. 1 2 http://dx.doi.org/10.1787/888932916287 1.8.2. Trends in low birth weight infants, selected OECD countries, 1990-2011 Source: OECD Health Statistics 2013, http://dx.doi.org/10.1787/health-data-en. 1 2 http://dx.doi.org/10.1787/888932916306 05101520 -50 0 50 100 3.2 4.1 4.2 4.4 4.6 5.2 5.2 5.6 5.7 5.9 5.9 6.2 6.2 6.2 6.4 6.6 6.7 6.8 6.8 6.9 6.9 7.0 7.0 7.0 7.1 7.6 7.8 8.1 8.1 8.1 8.3 8.4 8.5 8.6 9.6 10.0 11.1 13.2 27.6 11.0 10 14 -2 0 0 24 100 -31 0 9 -5 19 13 2 25 18 24 15 22 21 23 35 4 15 27 38 73 40 13 13 48 -9 0 52 67 22 -13 % change over the period% of newborns weighing less than 2 500 g 2011 Change 1990-2011 Greece Turkey Italy Czech Rep. Brazil Hungary Mexico Japan Austria Denmark Israel United States Portugal United Kingdom Belgium Canada Australia Switzerland Netherlands Spain Slovak Rep. Luxembourg France OECD34 Germany Korea Poland Russian Fed. Chile New Zealand Slovenia Indonesia South Africa India Iceland Finland Sweden Estonia Norway Ireland n.a. n.a. n.a. 2 3 4 5 6 7 8 9 10 1990 1995 2000 2005 2010 Japan Korea % of newborns weighing less than 2 500 g SpainPortugal OECD
  35. 35. HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 201340 1. HEALTH STATUS 1.9. Perceived health status Most OECD countries conduct regular health surveys which allow respondents to report on different aspects of their health. A commonly asked question relates to self- perceived health status, of the type: “How is your health in general?”. Despite the subjective nature of this question, indicators of perceived general health have been found to be a good predictor of people’s future health care use and mortality (DeSalvo et al., 2005; Bond et al., 2006). For the purpose of international comparisons, cross-country variations in perceived health status are difficult to inter- pret because responses may be affected by the formulation of survey questions and responses, and by social and cultural factors. Since they rely on the subjective views of the respondents, self-reported health status will reflect cultural biases or other influences. With these limitations in mind, in almost all OECD coun- tries, a majority of the adult population reports their health as good or better (Figure 1.9.1; left panel). The United States, New Zealand and Canada are the three leading countries, with about nine out of ten people reporting to be in good health. However, the response categories offered to survey respondents in these three countries are different from those used in European countries and Asian OECD countries, which introduce an upward bias in the results (see box on “Definition and comparability”). On the other hand, less than half of adults in Japan, Korea and Portugal rate their health as good or very good. The proportion is also relatively low in Estonia, Hungary, Poland, Chile and the Czech Republic, where less than 60% of adults consider themselves to be in good health. The percentage of adults rating their health as good or very good has remained fairly stable over the past few decades in most countries, although Japan has seen some decline since the mid-1990s. In all OECD countries, men are more likely than women to report being in good health, except in Australia where the proportion is equal. The gender gap is especially large in Chile, Portugal and Turkey (Figure 1.9.1; right panel). There are also large disparities in self-reported health across different socio-economic groups, as measured for instance by income level. Figure 1.9.2 shows that, in all countries, people with a lower level of income tend to report poorer health than people with higher income, although the gap varies. On average across OECD countries, nearly 80% of people in the highest income quintile reports being in good health, compared with just over 60% for peo- ple in the lowest income group. These disparities may be explained by differences in living and working conditions, as well as differences in health-related lifestyles (e.g., smoking, harmful alcohol drinking, physical inactivity, and obesity problems). In addition, people in low-income households may have more limited access to certain health services, for financial or non-financial reasons (see Chapter 6 on “Access to care”). It is also possible that the causal link goes the other way around, with poor health status in the first place leading to lower employment and lower income. Greater emphasis on public health and disease prevention among disadvantaged groups, and improving access to health services may contribute to further improvements in population health status and reducing health inequalities. Definition and comparability Perceived health status reflects people’s overall per- ception of their health, including both physical and psychological dimensions. Typically ascertained through health interview surveys, respondents are asked a question such as: “How is your health in gen- eral? Is it very good, good, fair, poor, very poor.” OECD Health Statistics provides figures related to the propor- tion of people rating their health to be “good/very good” combined. Caution is required in making cross-country compar- isons of perceived health status, for at least two rea- sons. First, people’s assessment of their health is subjective and can be affected by factors such as cul- tural background and national traits. Second, there are variations in the question and answer categories used to measure perceived health across surveys and countries. In particular, the response scale used in the United States, Canada, New Zealand and Australia is asymmetric (skewed on the positive side), including the following response categories: “excellent, very good, good, fair, poor.” The data in OECD Health Statistics refer to respondents answering one of the three posi- tive responses (“excellent, very good or good”). By contrast, in most other OECD countries, the response scale is symmetric, with response categories being: “very good, good, fair, poor, very poor.” The data reported from these countries refer only to the first two categories (“very good, good”). Such a difference in response categories biases upward the results from those countries that are using an asymmetric scale by about 5-8%. Self-reported health by income level is reported for the first quintile (lowest 20% of income group) and the fifth quintile (highest 20%). Depending on the sur- veys, the income may relate either to the individual or the household (in which case the income is equiv- alised to take into account the number of persons in the household).
  36. 36. 1. HEALTH STATUS 1.9. Perceived health status HEALTH AT A GLANCE 2013: OECD INDICATORS © OECD 2013 41 1.9.1. Percentage of adults reporting to be in good health, 2011 (or nearest year) 1. Results for these countries are not directly comparable with those for other countries, due to methodological differences in the survey questionnaire resulting in an upward bias. Source: OECD Health Statistics 2013 (EU-SILC for European countries), http://dx.doi.org/10.1787/health-data-en. 1 2 http://dx.doi.org/10.1787/888932916325 1.9.2. Perceived health status by income level, 2011 (or nearest year) Note: Countries are ranked in descending order of perceived health status for the whole population. 1. Results for these countries are not directly comparable with those for other countries, due to methodological differences in the survey questionnaire resulting in an upward bias. Source: OECD Health Statistics 2013 (EU-SILC for European countries), http://dx.doi.org/10.1787/health-data-en. 1 2 http://dx.doi.org/10.1787/888932916344 20406080100 20 40 60 80 100 89.5 89.3 88.2 85.4 83.4 81.5 81.3 79.9 77.8 77.5 76.4 76.4 75.3 73.6 73.3 72.6 71.0 69.4 69.1 69.0 67.6 67.2 65.5 64.8 64.7 63.4 60.5 59.6 59.1 57.8 56.1 51.9 49.7 36.8 30.0 88.9 88.9 87.6 85.4 83.1 79.5 78.6 78.0 76.1 76.5 73.5 74.1 72.3 71.7 71.1 70.2 69.0 67.6 67.7 66.6 64.4 62.3 64.2 63.3 61.7 59.0 57.6 57.3 51.4 54.9 52.5 50.1 44.6 33.5 28.6 90.2 89.7 88.8 85.4 83.6 83.5 84.0 81.8 79.4 78.5 79.6 79.0 78.3 75.5 75.4 75.1 73.1 71.3 70.5 71.5 71.1 72.3 66.9 66.4 67.9 68.1 63.5 62.5 67.3 61.1 60.1 54.5 55.3 40.2 31.5 % of population aged 15 and over% of population aged 15 and over Switzerland Sweden United States¹ New Zealand¹ Canada¹ Australia¹ Ireland Israel¹ Iceland United Kingdom Netherlands Greece Spain Belgium Slovak Rep. Norway Luxembourg Denmark Austria Finland OECD34 Czech Rep. Chile¹ Poland Hungary Estonia France Turkey Mexico Germany Italy Portugal Korea Japan Slovenia Total population Women Men 0 10 20 30 40 50 60 70 80 90 100 % of population aged 15 and over United States¹ New Zealand¹Canada¹ Australia¹Ireland Israel¹ SwitzerlandSwedenIceland United Kingdom NetherlandsGreece SpainBelgiumNorway Luxem bourgDenm arkAustriaFinlandOECD33FranceTurkeyGerm any Italy SlovakRep.Slovenia Czech Rep. Chile¹PolandHungaryEstoniaPortugal Korea Japan Lowest income Highest income

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